{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:C7ZQ66PCBOONV62FBD5G6YWT7H","short_pith_number":"pith:C7ZQ66PC","schema_version":"1.0","canonical_sha256":"17f30f79e20b9cdafb4508fa6f62d3f9f1f0663cc07ad933508c1ee0b5fc8bc0","source":{"kind":"arxiv","id":"2607.15912","version":1},"attestation_state":"computed","paper":{"title":"HETA++: Global Structure-from-Motion with Hybrid Explicit Translation Averaging","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hainan Cui, Mengqi Rong, Peilin Tao, Shuhan Shen","submitted_at":"2026-07-17T12:40:01Z","abstract_excerpt":"Global Structure-from-Motion (SfM) offers advantages over incremental methods in terms of efficiency and error distribution. However, the task of translation averaging remains challenging. Many existing methods rely solely on relative translations or feature tracks, which either degrade under collinear camera motion or are susceptible to outliers. In this paper, we propose a novel hybrid explicit translation averaging framework that incorporates both relative translations and feature tracks. Specifically, we first refine the relative translations using global camera rotations and remove global"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2607.15912","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-17T12:40:01Z","cross_cats_sorted":[],"title_canon_sha256":"d35ac2dbb3eba432b265f0e6aa25a3e9b7d378ff1c2b49224377819986e15108","abstract_canon_sha256":"2fabe9d033800f3b09c22060f58c1ab7860cb9b2b77c4c9a9a8ee3f8a9249260"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-20T01:19:17.006532Z","signature_b64":"lmZdue1uVpDORonl6FUu4HDgYjxix6fwbCICN1DOmcArQwWQwvTeJTe+d7iDyH5Q/OPKYE5pWuTTxLFNO6scAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17f30f79e20b9cdafb4508fa6f62d3f9f1f0663cc07ad933508c1ee0b5fc8bc0","last_reissued_at":"2026-07-20T01:19:17.005677Z","signature_status":"signed_v1","first_computed_at":"2026-07-20T01:19:17.005677Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"HETA++: Global Structure-from-Motion with Hybrid Explicit Translation Averaging","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hainan Cui, Mengqi Rong, Peilin Tao, Shuhan Shen","submitted_at":"2026-07-17T12:40:01Z","abstract_excerpt":"Global Structure-from-Motion (SfM) offers advantages over incremental methods in terms of efficiency and error distribution. However, the task of translation averaging remains challenging. Many existing methods rely solely on relative translations or feature tracks, which either degrade under collinear camera motion or are susceptible to outliers. In this paper, we propose a novel hybrid explicit translation averaging framework that incorporates both relative translations and feature tracks. Specifically, we first refine the relative translations using global camera rotations and remove global"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.15912","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.15912/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.15912","created_at":"2026-07-20T01:19:17.006110+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.15912v1","created_at":"2026-07-20T01:19:17.006110+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.15912","created_at":"2026-07-20T01:19:17.006110+00:00"},{"alias_kind":"pith_short_12","alias_value":"C7ZQ66PCBOON","created_at":"2026-07-20T01:19:17.006110+00:00"},{"alias_kind":"pith_short_16","alias_value":"C7ZQ66PCBOONV62F","created_at":"2026-07-20T01:19:17.006110+00:00"},{"alias_kind":"pith_short_8","alias_value":"C7ZQ66PC","created_at":"2026-07-20T01:19:17.006110+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/C7ZQ66PCBOONV62FBD5G6YWT7H","json":"https://pith.science/pith/C7ZQ66PCBOONV62FBD5G6YWT7H.json","graph_json":"https://pith.science/api/pith-number/C7ZQ66PCBOONV62FBD5G6YWT7H/graph.json","events_json":"https://pith.science/api/pith-number/C7ZQ66PCBOONV62FBD5G6YWT7H/events.json","paper":"https://pith.science/paper/C7ZQ66PC"},"agent_actions":{"view_html":"https://pith.science/pith/C7ZQ66PCBOONV62FBD5G6YWT7H","download_json":"https://pith.science/pith/C7ZQ66PCBOONV62FBD5G6YWT7H.json","view_paper":"https://pith.science/paper/C7ZQ66PC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.15912&json=true","fetch_graph":"https://pith.science/api/pith-number/C7ZQ66PCBOONV62FBD5G6YWT7H/graph.json","fetch_events":"https://pith.science/api/pith-number/C7ZQ66PCBOONV62FBD5G6YWT7H/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/C7ZQ66PCBOONV62FBD5G6YWT7H/action/timestamp_anchor","attest_storage":"https://pith.science/pith/C7ZQ66PCBOONV62FBD5G6YWT7H/action/storage_attestation","attest_author":"https://pith.science/pith/C7ZQ66PCBOONV62FBD5G6YWT7H/action/author_attestation","sign_citation":"https://pith.science/pith/C7ZQ66PCBOONV62FBD5G6YWT7H/action/citation_signature","submit_replication":"https://pith.science/pith/C7ZQ66PCBOONV62FBD5G6YWT7H/action/replication_record"}},"created_at":"2026-07-20T01:19:17.006110+00:00","updated_at":"2026-07-20T01:19:17.006110+00:00"}